1. Field of the Invention
The present invention relates to an image processing method, an image processing apparatus, and an image processing program, for extracting high frequency components from digital photographic images.
2. Description of the Related Art
In the field of image processing of digital photographic images, extraction of high frequency components is a process that is performed often. For example, various image processes are administered on digital image data sets to improve the image qualities thereof prior to printing. The digital image data sets are obtained by photoelectrically reading out photographic images, which are recorded on negative films or reversal films, with scanners, or by photography with digital still cameras (DSC's) . A blur correction process, for removing blur from blurred images, is an example of such an image process.
A blur correction method has been proposed, in which high -frequency components within images are extracted, emphasized, then added to the original images (in Mikio Takagi, Haruhisa Shimoda, Ed. “Handbook of Image Analysis”, pp. 549, Tokyo University Press, for example). Specifically, this method is performed according to the following Formula (1).S′=Sorg+β·(Sorg−Sus)  (1)
wherein                S′: corrected image        Sorg: original image        Sus: blurred mask image        β: emphasizing coefficient        
Here, Sus is an image obtained by applying a blurred mask on the original image Sorg, and represents the low frequency components of the original image Sorg. For this reason, (Sorg−Sus) represents the high frequency components of the original image Sorg. As can be understood from Formula (1) above, the corrected image S′ is the sum of the original image Sorg, and the high frequency components of the original image Sorg, which have been emphasized with the coefficient β. Sufficient extraction of the high frequency components from the original image is a factor that affects the effectiveness of blur correction.
A commonly employed technique for extracting high frequency components from digital photographic images will be described. First, a blurred mask image is obtained by applying a blur mask, for example, a blur filter which is a low pass filter, on the original image. Then, the blurred mask image is subtracted from the original image, to extract the high frequency components. The time required for operations increases as the size of the blur filter increases. Therefore, filters having sizes of 5 taps to 7 taps are generally employed.
U.S. Pat. No. 6,289,133 discloses a method, by which high frequency components are extracted at high speed. In this method, original images are reduced in size to obtain reduced images. Then, a blur mask filter process is administered on the reduced images. Finally, the reduced images, on which the blur mask process has been administered, are enlarged to the size of the original images.
However, in cases that the degree of blur within original images is great, there are few high frequency components included therein. Therefore, if a blur filter of a conventional size is employed to extract high frequency components, the number of extractable high frequency components is low. For example, consider the case of a blurred image having the frequency characteristics illustrated in FIG. 12A. If high frequency components are extracted from this image employing a 5 tap filter having the frequency characteristics illustrated in FIG. 12B, the extracted high frequency components are those illustrated in FIG. 12C. As illustrated in FIG. 12C, the number of high frequency components extracted from a blurred image, such as that illustrated in FIG. 12A, is extremely low. For this reason, if the extracted high frequency components are employed to perform the aforementioned blur correction process, favorable correction results cannot be obtained.
Applying a blur filter of a large size may be considered, in order to sufficiently extract high frequency components from blurred images having great degrees of blur. However, the application of such filters will increase the time required for operations, and therefore would be inefficient.
Applying the method disclosed in U.S. Pat. No. 6,289,133, that is, reducing the size of the blurred image to obtain a reduced image, then extracting high frequency components from the reduced image, may also be considered. However, there is a possibility that high frequency components will be lost due to reduction, in the case of images that do not have great degrees of blur. As a result, high frequency components may not be sufficiently extracted, in a similar manner.